Research On The Optimization Of Shearer Adaptive Cutting In Coal Seam Containing Gangue

As an important underground fully mechanized mining equipment,the drum shearer is of great significance for realizing efficient underground mining.Many scholars at home and abroad have conducted a lot of research on the realization of intelligent cutting of shearers,and their research focuses on the drum cutting.In the process,the identification of coal and rock state and the optimization of the cutting performance of the drum are less studied.In order to realize the intelligent and efficient cutting of different forms of gangue by the shearer,this paper proposes a set of adaptive cutting control scheme and process for the coal seam with gangue.Taking the contour shearer as the research object,the discrete element numerical simulation method is adopted.,the cutting simulation of different shapes of gangue coal wall was carried out.Geometric analysis of the gangue cutting process is carried out and it is divided into two stages;the feature extraction of the torque signal in the first stage is carried out,and three neural network prediction models are established to predict the gangue inclination angle and the gangue thickness;The optimization model of shearer motion parameters was established,and the drum motion parameters in the second stage were optimized according to the identification results of the gangue shape identification in the first stage.The smaller gangue wall is optimized with the rated motor power cutting and cutting ratio energy consumption as the target,and the gangue wall with larger inclination angle is optimized with the motor rated power as the target.The optimized drum motion parameters are used for cutting simulation to verify the feasibility of the proposed scheme,which provides an important reference for efficient cutting and intelligent cutting of gangue coal seams.The research results show that the shape of the gangue has an important influence on the torque change during the cutting process of the drum.When cutting the horizontal gangue,the drum torque changes smoothly,while when cutting the inclined gangue,the drum torque increases first and then decreases.change trend,and the torque change in the increasing process is more severe than that in the decreasing process;the thickness of the gangue does not affect the change trend of the drum torque,but with the increase of the thickness of the gangue,the specific energy consumption of the drum cutting first increases and then decreases;For the inclined gangue,the direction of movement of the drum has a certain influence on the cutting performance of the shearer,the cutting energy consumption is slightly lower when cutting from the side with the smaller gangue inclination angle;when the traction speed increases,the coal seams with different shapes of gangue are The motor power,cutting torque and torque fluctuation coefficient of the lower drum will increase,but the cutting specific energy consumption and cutting time will decrease.The cutting ratio energy consumption and torque fluctuation coefficient increase;BP neural network,Elman neural network and GRNN neural network can effectively identify the inclination angle and thickness of the gangue according to the torque characteristics of the first stage drum.The prediction effect of the gangue inclination angle is good,the maximum error of the gangue inclination angle in the detection group is 6.41°,and the BP neural network has a better prediction effect on the thickness of the gangue,and the maximum error of the gangue thickness in the detection group is 21.87mm;the optimized inspection model roller cutting The performance has been effectively improved,and the cutting power of the drum is closer to the rated value of the motor,which improves the pertinence of the optimization scheme.It is found that the recognition accuracy of the gangue shape and the prediction accuracy of the cutting motor power are important factors affecting the model optimization results.The research content of this paper provides a feasible solution for shearers to efficiently cut different forms of gangue-incorporated coal seams,and provides an important reference for the realization of shearer intelligent cutting of ganguecontaining coal seams.The paper has 68 figures,30 tables,and 72 references.